PANDA: a pipeline toolbox for analyzing brain diffusion images
Diffusion magnetic resonance imaging (dMRI) is widely used in both scientific research and clinical practice in in-vivo studies of the human brain. While a number of post-processing packages have been developed, fully automated processing of dMRI datasets remains challenging. Here, we developed a MA...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2013-02-01
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| Series: | Frontiers in Human Neuroscience |
| Subjects: | |
| Online Access: | http://journal.frontiersin.org/Journal/10.3389/fnhum.2013.00042/full |
| _version_ | 1818280529757208576 |
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| author | Zaixu eCui Suyu eZhong Pengfei eXu Gaolang eGong Yong eHe |
| author_facet | Zaixu eCui Suyu eZhong Pengfei eXu Gaolang eGong Yong eHe |
| author_sort | Zaixu eCui |
| collection | DOAJ |
| description | Diffusion magnetic resonance imaging (dMRI) is widely used in both scientific research and clinical practice in in-vivo studies of the human brain. While a number of post-processing packages have been developed, fully automated processing of dMRI datasets remains challenging. Here, we developed a MATLAB toolbox named Pipeline for Analyzing braiN Diffusion imAges (PANDA) for fully automated processing of brain diffusion images. The processing modules of a few established packages, including FMRIB Software Library (FSL), Pipeline System for Octave and Matlab (PSOM), Diffusion Toolkit and MRIcron, were employed in PANDA. Using any number of raw dMRI datasets from different subjects, in either DICOM or NIfTI format, PANDA can automatically perform a series of steps to process DICOM/NIfTI to diffusion metrics (e.g., FA and MD) that are ready for statistical analysis at the voxel-level, the atlas-level and the Tract-Based Spatial Statistics (TBSS)-level and can finish the construction of anatomical brain networks for all subjects. In particular, PANDA can process different subjects in parallel, using multiple cores either in a single computer or in a distributed computing environment, thus greatly reducing the time cost when dealing with a large number of datasets. In addition, PANDA has a friendly graphical user interface (GUI), allowing the user to be interactive and to adjust the input/output settings, as well as the processing parameters. As an open-source package, PANDA is freely available at http://www.nitrc.org/projects/panda/. This novel toolbox is expected to substantially simplify the image processing of dMRI datasets and facilitate human structural connectome studies. |
| first_indexed | 2024-12-12T23:50:41Z |
| format | Article |
| id | doaj.art-9965d432dcdf4c5fa0fe44a37ece828c |
| institution | Directory Open Access Journal |
| issn | 1662-5161 |
| language | English |
| last_indexed | 2024-12-12T23:50:41Z |
| publishDate | 2013-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Human Neuroscience |
| spelling | doaj.art-9965d432dcdf4c5fa0fe44a37ece828c2022-12-22T00:06:43ZengFrontiers Media S.A.Frontiers in Human Neuroscience1662-51612013-02-01710.3389/fnhum.2013.0004234880PANDA: a pipeline toolbox for analyzing brain diffusion imagesZaixu eCui0Suyu eZhong1Pengfei eXu2Gaolang eGong3Yong eHe4Beijing Normal UniversityBeijing Normal UniversityBeijing Normal UniversityBeijing Normal UniversityBeijing Normal UniversityDiffusion magnetic resonance imaging (dMRI) is widely used in both scientific research and clinical practice in in-vivo studies of the human brain. While a number of post-processing packages have been developed, fully automated processing of dMRI datasets remains challenging. Here, we developed a MATLAB toolbox named Pipeline for Analyzing braiN Diffusion imAges (PANDA) for fully automated processing of brain diffusion images. The processing modules of a few established packages, including FMRIB Software Library (FSL), Pipeline System for Octave and Matlab (PSOM), Diffusion Toolkit and MRIcron, were employed in PANDA. Using any number of raw dMRI datasets from different subjects, in either DICOM or NIfTI format, PANDA can automatically perform a series of steps to process DICOM/NIfTI to diffusion metrics (e.g., FA and MD) that are ready for statistical analysis at the voxel-level, the atlas-level and the Tract-Based Spatial Statistics (TBSS)-level and can finish the construction of anatomical brain networks for all subjects. In particular, PANDA can process different subjects in parallel, using multiple cores either in a single computer or in a distributed computing environment, thus greatly reducing the time cost when dealing with a large number of datasets. In addition, PANDA has a friendly graphical user interface (GUI), allowing the user to be interactive and to adjust the input/output settings, as well as the processing parameters. As an open-source package, PANDA is freely available at http://www.nitrc.org/projects/panda/. This novel toolbox is expected to substantially simplify the image processing of dMRI datasets and facilitate human structural connectome studies.http://journal.frontiersin.org/Journal/10.3389/fnhum.2013.00042/fullDTInetworkdiffusion MRIconnectomestructural connectivitypipeline |
| spellingShingle | Zaixu eCui Suyu eZhong Pengfei eXu Gaolang eGong Yong eHe PANDA: a pipeline toolbox for analyzing brain diffusion images Frontiers in Human Neuroscience DTI network diffusion MRI connectome structural connectivity pipeline |
| title | PANDA: a pipeline toolbox for analyzing brain diffusion images |
| title_full | PANDA: a pipeline toolbox for analyzing brain diffusion images |
| title_fullStr | PANDA: a pipeline toolbox for analyzing brain diffusion images |
| title_full_unstemmed | PANDA: a pipeline toolbox for analyzing brain diffusion images |
| title_short | PANDA: a pipeline toolbox for analyzing brain diffusion images |
| title_sort | panda a pipeline toolbox for analyzing brain diffusion images |
| topic | DTI network diffusion MRI connectome structural connectivity pipeline |
| url | http://journal.frontiersin.org/Journal/10.3389/fnhum.2013.00042/full |
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